Honestly? I'm disappointed with reviewers...(Rating: 5)
Giving this book a bad review because:
a) you had a bad instructor for the course
b) you find the material difficult
c) you can't understand pseudo-code

are not what I would call constructive or worthwhile critiques of the text of this excellent book. PLEASE society, PLEASE understand that some topics you have to actually WORK at understanding. It won't be spoon fed to you.

It seems moreso with Computer Science majors than other majors (I'm an electrical engineer undergrad, comp sci grad student) that they whine and whine and whine about the math or about it being difficult to actually have to work to understand something.

Oh my GOODNESS!!!! It's hard? Well, BLAME THE BOOK.

Rant over.

This book is amazing. It's the bible of algorithms and, to some extent, data structures. If you're not aforementioned whiners, feel free to buy this book, work hard, and learn a lot! There's not a better book out there in my experience.

Good description(Rating: 4)
I found this book to be very good in explaining the algorithms. The language is too complicated and long-winded. The book is an excellent accompaniment to lectures, but not very good on its own.

It's a standard, but...(Rating: 3)
I have deep respect for math and people who can make sense out of it, but I am really slow thinker and this book simply overwelmed me. I don't know what is so wrong with having some problems answered. I learned to solve them by going through step by step examples, which this book lacks. After "Single Variable Calculus" by Stewart and "Discrete Mathematics" by Epp, this book looks quite arrogant. Each page like a statement: "You stupid, don't touch me!" I did not like pseudo-code and I did not find it's clear and helpful. This book has a lot of good stuff, but I don't believe that making things hard makes them more important and full of sense. After all , I think everything can be divided into simple ideas , and then explained. Like those "divide and conquer" algorithms that authors describe. It's pitty that they themselves don't practice what they preach.

Don't buy it unless you're forced. Get Robert Sedgewick's books. They balance well math and programming and have nicely done code snippets.

Poorly written with lack of ways to test yourself(Rating: 2)
While many have noted how Thomas Corwen and his co-authors have added a scholarly touch to this subject with plenty of proofs it does not make for a good text. One can argue that this book should supplement the instructor's teachings. That would be fine except for the fact that there are no answers to the problems. Therefore, a student has no idea if he or she is on the right track.
To this end Corwen snidely replies on his website that any student asking for the answer will have his or her name posted as a potential cheater since Corwen believes that instructors should be able to use his problems as homework. Here's an idea, how about instructors developing their own problems!
Corwen also does not relate the material in plain English as someone like Frank Carrano does. There are other sources of many of the concepts like binary search trees, sorting algorithms, O-notation. The only thing Corwen is adding is lots of proof and mathematical shorthand.
If you are interested in the mathematical concepts behind the algorithms this is a fine introduction. If you are interested in the algorithmic concepts, this is not for you. Ultimately if you are a student whose instructor will be using this book, you have no choice about buying it. If you are an instructor, however, look at another book to supplement your teachings.

Concise and Clear, No. Why not both?(Rating: 1)
There are a number of reviewers who proclaim that the language agnostic nature of this book, in addition to it's erudite tone, more than compensate for the (artificial) learning curve.

I beg to differ. Being an actuary, I recognize that this book's code snippets are written in a variation of APL. APL is hardly a self-evident programming language (read-only is a more accurate description).

While computer science cognoscenti might decry spoon-feeding, there's nothing wrong with being *concise and clear* concurrently. Indeed, the truly great books in the hard sciences are both easy to read and rigorous at the same time. If pedants would get off of their high horses for a moment, they would probably admit this much (heck, who wouldn't?).

Rigor at the expense of clarity may appeal to intellectual snobs (who live for the material, god help them), and clarity at the expense of rigor may appeal to beginners, but WHY NOT HAVE BOTH?

While this book covers a good deal of ground, it does so at the expense of clarity. A canonical book would have both rigor and clarity, and this book doesn't. It's as simple as that.

The sordid truth about this book is that Professors tend to assign it as reading material with the expectation that students will rely primarily on class notes and then use the book as a reference of sorts (or as a source of homework problems). Most of the graduate courses that I've taken follow this approach.

Having said all this, academia is essentially a small and sterile refuge for people who couldn't hack the real world. Take your courses, if you must, and then go out and get a life. In the end, most journals end up in the waste basket. Your time on this planet is short, don't waste it cloistered in a library!

trust me on this...